It is known to diagnose a mechanical condition of a pump by monitoring vibrations and/or noise. However, these methods are expensive and can be difficult to implement on-site as they require additional transducers as well as elaborate signal processing devices. Furthermore, in order to perform a complete monitoring of the pump would require a large number of vibration transducers at locations, for example bearings, gearboxes, stator frame, etc.
A self-diagnosis method for a dry-vacuum pump is known from U.S. Pat. No. 8,721,295. The method comprises monitoring a current of a motor for rotating a rotor of the pump in conjunction a system pressure. The method seeks to identify one-off events in the form of peaks in the measured current; or to determine when the measured current exceeds a predefined threshold.
US 2008/0294382 discloses a method and apparatus for pump fault prediction. A model may be defined for managing a plurality of qualitative variables (e.g., process variables) from a relatively large number of pumps with improved predictability. To define the model, a principal component analysis (PCA) may be used to consider the correlation of multivariate data. A management variable can be selected to represent variations of the selected principal components. A controller may determine that the pump is operating in an abnormal state if the management variable exceeds an upper control line. A sensor can be connected to the pump to collect data in real time for qualitative variables associated with the pump and a corresponding semiconductor fabricating process. A replacement time for a pump may be predicted before a pump fault actually occurs by using an information system to collect data related to the process variables and statistically processing the collected data.